December 23, 2024
Headlines

LLM

IBM AI Team Releases an Open-Source Family of Granite Code Models for Making Coding Easier for Software Developers

Chibuike Mba05 mins

IBM has made a great advancement in the field of software development by releasing a set of open-source Granite code models designed to make coding easier for people everywhere. This action stems from the realization that, although software plays a critical role in contemporary society, the process of coding is still difficult and time-consuming. Even seasoned engineers frequently struggle to keep learning new things, adjust to new languages, and solve challenging problems.

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Researchers from Princeton and Meta AI Introduce ‘Lory’: A Fully-Differentiable MoE Model Designed for Autoregressive Language Model Pre-Training

Chibuike Mba06 mins

Mixture-of-experts (MoE) architectures use sparse activation to initial the scaling of model sizes while preserving high training and inference efficiency. However, training the router network creates the challenge of optimizing a non-differentiable, discrete objective despite the efficient scaling by MoE models. Recently, an MoE architecture called SMEAR was introduced, which is fully non-differentiable and merges experts gently in the parameter space. SMEAR is very efficient, but its effectiveness is limited to small-scale fine-tuning experiments on downstream classification tasks.

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Nvidia Blackwell GB200

Introducing the NVIDIA Blackwell Platform: Unveiling the B200, the Flagship AI Chip, for Pioneering Computing and Generative AI

Chibuike Mba04 mins

GTC—Powering a new era of computing, NVIDIA on Monday 18th of March 2024 announced that the NVIDIA Blackwell platform has arrived — enabling organizations everywhere to build and run real-time generative AI on trillion-parameter large language models at up to 25x less cost and energy consumption than its predecessor.

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GPT-4

Navigating Autonomous Hypothesis Verification: Language Models’ Journey with Minimal Guidance

Chibuike Mba04 mins

GPT-4’s role in autonomously navigating the hypothesis verification process signifies a step towards a more independent form of research. As we navigate the challenges identified in this study, the collaboration between language models and human expertise holds the key to unlocking the full potential of autonomous research. Stay tuned for further advancements in this exciting frontier.

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The LLM Revolution: From ChatGPT to Industry Adoption

Navigating the Complex Landscape of Large Language Models (LLMs) in AI: Potential, Pitfalls, and Responsibilities

Chibuike Mba06 mins

Artificial Intelligence (AI) is currently experiencing a significant surge in popularity. Following the viral success of OpenAI’s conversational agent, ChatGPT, the tech industry has been abuzz with excitement about Large Language Models (LLMs), the technology that powers ChatGPT. Tech giants like Google, Meta, and Microsoft, along with well-funded startups such as Anthropic and Cohere, have all launched their own LLM products. Companies across various sectors are rushing to integrate LLMs into their services, with OpenAI counting customers like fintech companies using them for customer service chatbots, edtech platforms like Duolingo and Khan Academy for educational content generation, and even video game companies like Inworld for providing dynamic dialogue for non-playable characters (NPCs). With widespread adoption and a slew of partnerships, OpenAI is on track to achieve annual revenues exceeding one billion dollars.

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Generative AI

Unlocking Enterprise Success: 10 Impactful Use Cases of NLP Generative AI

Chibuike Mba05 mins

In a world increasingly dominated by artificial intelligence (AI) and the promise of groundbreaking applications like ChatGPT, enterprises are seeking concrete ways to harness AI’s potential for tangible benefits. Through our extensive collaborations with leading technology consulting firms and direct interactions with businesses, we’ve pinpointed 10 Natural Language Processing (NLP) and generative AI use cases that not only resolve longstanding organizational challenges but are also exceptionally well-suited for AI solutions, given today’s cutting-edge technology.

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